On direction finding with unknown noise covariance

Author

Friedlander, Benjamin ; Weiss, Anthony J.

Author_Institution

Dept. of Electr. & Comput. Eng., California Univ., Davis, CA, USA

Volume

2

fYear

1994

fDate

31 Oct-2 Nov 1994

Firstpage

780

Abstract

A class of direction finding methods which operate in the presence of correlated noise with an unknown covariance matrix is presented. The approach is based on joint estimation of the directions of arrival and the parameters of a model for the noise covariance matrix, using a maximum likelihood estimator, its suboptimal version or other methods. Formulas for evaluating the maximal number of identifiable noise parameters are also derived. Using the Cramer Rao bound we study the degradation in DOA estimation accuracy due to the estimation of the noise parameters

Keywords

Gaussian noise; covariance matrices; direction-of-arrival estimation; maximum likelihood estimation; Cramer Rao bound; DOA estimation accuracy; Gaussian noise; direction finding methods; directions of arrival; joint estimation; maximum likelihood estimator; noise covariance matrix; noise parameter estimation; suboptimal MLE; Covariance matrix; Cramer-Rao bounds; Direction of arrival estimation; Linear matrix inequalities; Maximum likelihood detection; Maximum likelihood estimation; Multiple signal classification; Radar signal processing; Radio frequency; Sonar;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 1994. 1994 Conference Record of the Twenty-Eighth Asilomar Conference on

Conference_Location

Pacific Grove, CA

ISSN

1058-6393

Print_ISBN

0-8186-6405-3

Type

conf

DOI

10.1109/ACSSC.1994.471568

Filename

471568